Search Results for "vulnerable machine"

...By leveraging archived data, waybackurls helps identify hidden attack surfaces, legacy APIs, and forgotten resources that could be vulnerable. Its design is intentionally simple and efficient, focusing on delivering large volumes of URLs quickly with minimal configuration. The output can be combined with other tools for further analysis, such as filtering parameters or probing endpoints.

VPLE (Linux) Vulnerable Pentesting Lab Environment VPLE is an Intentionally Vulnerable Linux Virtual Machine. This VM can be used to conduct security training, test security tools, and practice common penetration testing Labs. In VPLE bunch of labs are Available. NOTE:- "Only run in VMWare Pls Don’t run in VirtualBox" The default login and password is administrator: password.

VulnOS are a series of deliberately vulnerable operating systems packed as virtual machines to teach Offensive IT Security and to enhance penetration testing skills. For educational purposes!

An XML External Entity attack is a type of attack against an application that parses XML input. This attack occurs when XML input containing a reference to an external entity is processed by a weakly configured XML parser. This attack may lead to the disclosure of confidential data, denial of service, port scanning from the perspective of the machine where the parser is located. This zipped Ubuntu VM is set up as a Capture the Flag with those that successfully exploit the XXE vulnerability...

the goal is to get the flag in the root directory. /root/

Adobe Malware Classifier is a command-line tool that lets antivirus analysts, IT administrators, and security researchers quickly and easily determine if a binary file contains malware, so they can develop malware detection signatures faster, reducing the time in which users' systems are vulnerable. Malware Classifier uses machine learning algorithms to classify Win32 binaries – EXEs and DLLs – into three classes: 0 for “clean,” 1 for “malicious,” or “UNKNOWN.” The tool was developed using models resultant from running the J48, J48 Graft, PART, and Ridor machine-learning algorithms on a dataset of approximately 100,000 malicious programs and 16,000 clean programs. ...